Pricing Strategy

Cost-plus (cost × markup %) is simple but leaves money on the table. You charge the same to customers with different willingness-to-pay. Value-based pricing anchors price to customer value (ROI, time savings, pain point severity). If your $100 cost product saves a customer $500/year, you could charge $300-400 and both win. Hybrid approach: use cost-plus as a floor (must exceed contribution margin), then overlay value-based to set ceiling. A/B test the delta — many companies find 20-40% revenue lift by shifting from cost-plus to value-based.

B2B: longer sales cycles, high deal sizes ($10k-$1M+), willingness-to-pay varies wildly by company size/use case. Use value-based pricing (tie to customer ROI), three-tier packaging (Starter/Pro/Enterprise), and sales-assisted discounting. B2C: faster decisions, smaller deal sizes ($5-100), price-sensitive, homogeneous customer base. Use psychological pricing (anchoring, charm pricing $9.99, decoy effect), simple 2-3 tiers, and dynamic pricing (adjust by demand/segment). B2B2C (partner-enabled): add partner margin math into your pricing. Most common mistake: using one pricing playbook across both — misalignment.

Freemium (free core + paid premium): high adoption, low conversion (typically 1-5%), but long tail monetization for power users. Freemium works best for viral, low-friction products (Slack, Figma, Canva). Trial (free 14-30 days, full feature access): lower adoption but higher conversion (10-20%), works for higher-trust purchases. Pay-as-you-go (Stripe, Twilio): fair pricing, scales with customer value, attracts users who are cost-conscious. Hybrid: offer freemium + annual subscription option (annual = 20-40% discount). Measure: activation rate (sign-up → first active use) × conversion rate (free → paid) × net MRR. Freemium = high adoption + low conversion; trial = low adoption + high conversion — pick based on your unit economics.

Tools: (1) Van Westendorp Price Sensitivity Meter (4 questions: too cheap, bargain, expensive, too expensive → calculates optimal price range); (2) Gabor-Granger (show incrementally higher prices, stop when interested drops); (3) Conjoint analysis (customers choose between bundles at different prices, reveals preference weights). Anchoring: customers judge price against a reference point — list a higher 'recommended' price alongside your sale price (decoy). Avoid 'no anchor' condition (shows lowest WTP). Run WTP studies quarterly as your product matures. Most startups skip this and overprice by 20-50%, killing conversion — validate before launch.

Rule of thumb: Starter should serve 50-60% of customers (lower LTV but high volume); Pro 25-35% (growing businesses, willing to pay more); Enterprise 5-15% (largest customers, sales-assisted, custom pricing). Feature distribution: reserve high-value/differentiated features for higher tiers (e.g., SSO, API, dedicated support for Enterprise). Use 'good/better/best' not 'basic/plus/premium' (perceived value). Avoid too much feature cannibalization (if Starter does 95% of what Pro does, nobody upgrades). Test: start with 2 tiers, add Enterprise later. Common mistake: too many tiers (customer paralysis, support burden).

Anchoring: display a higher reference price (list/MSRP) next to your sale price — customers judge your price against it. Decoy effect: add a third (slightly worse, slightly cheaper) option between Starter/Pro — makes Pro look better by comparison. Both are ethical if real (MSRP was actual list price, decoy is real option), unethical if fabricated. Example: SaaS shows 'was $99/mo, now $69/mo' (truthful anchoring = good); shows '$99 crossed out but never was' (bad). Test: A/B compare 2-tier vs 3-tier packaging — typically 3-tier wins by 10-20% because of decoy effect. Monitor churn in decoy tier (should be 5-10% of revenue); if too high, it's bad decoy placement.

Metrics: (1) Conversion rate (CVR) — did unit economics improve? Don't just optimize for CVR, it can drop 30% with 50% price increase (win if MRR grows); (2) Customer lifetime value (LTV) — segment by price point, track cohort LTV 3-6 months out (some customers are happy to pay more AND more loyal); (3) Traffic source — some channels price-insensitive, others ultra-sensitive (paid search converts 5% at $99/mo, organic converts 15% at $49/mo); (4) Payback period — did CAC payback improve? (5) Churn — higher price = higher churn (common myth); often churn stays same or improves because screened customers are better fit. Common mistake: test price in vacuum (change price but not positioning/anchor/messaging) — changes to these confound results. Run price tests for 2-4 weeks minimum (longer for low-volume).